Influence of Consumer Psychology on Mobile Reviews and Their Persuasive Impact

The research therefore does an empirical literature review to build the theoretical framework based on the symptoms that it seeks to investigate in mobile phone reviews. This leads to the finding that psychological biases do not only have an impact on the content creation but also on the subsequent persuasion on further consumers. In method, the content analysis is used to analyze user reviews and sentiment analysis to examine the emotional and language features. Hypothesis testing is also carried out in order to assess the impact of structural variations to the reviews on decision-making in purchase scenarios. In particular, by analyzing empirical data, the study identifies that consumer reviews are not only full of experience descriptions but also contain various biases. For example, anchoring biases can be observed when the initial reference to the price of a particular mobile phone is made when performing a review, all subsequent information will be processed with a primary emphasis on the price. In reviews consumers confirm a first impression of product being positive or negative with focus on aspects reinforcing that initial impression. Another of such important factors towards influence is Availability heuristic whereby prospective buyers would be influenced more by those reviews readily available with rather salient experiences which could be explained by the Freshness and recency effect. It also explores how other aspects of the platform that differentiate them influence consumer behaviour including basic features like social proof, time factor about the reviews or the visibility of certain reviews as recommended reviews given by buyers with high engagement or those who passed through the verification process. These problems are especially true where algorithms are used to promote specific reviews, and therefore, make them more relevant to a potential buyer. The research presented here indicates that consumers are not averse to such biases and that like when reading the reviews, these biases impinge on the writing of the reviews as well. They also pointed out that while consumers who are familiar with these biases might be better off in terms of making more rational decisions, the ones who were not exposed to such biases might be influenced to easily by the so called ‘gut feeling’ reviews which are also those, which seem to get the most attention. Altogether, this study offers fine-grained timeworn and fresh insights into the relationship between consumer psychology and online content to map out how and to what extent psychological effects influence consumer-generated content and the importance of raising awareness and implementing different mitigations to help consumers make a more rational decision. A clear focus of the study is to examine platform-mediated factors and their impact in the review ecosystem. A prominent problem is that algorithms that are designed to promote ‘useful’ or ‘more informative’ product reviews may enhance prejudiced material, especially as their calibration is guided by engagement metrics rather than the quality of information. This means that about the quality of the reviews, it will not present a balanced view in its algorithms which are likely to mislead consumers to go for the engaging but informative or biased content. The study uses quantitative analysis with natural language processing, together with qualitative analysis and behavioral mimicking. It is possible to determine emotional and cognitive bias regularities of mass mobile phone reviews by using elements of sentiment analysis. Psycholinguistic modeling extends the examination of the connection between semantic and syntactic variables to review persuasiveness and may offer perceptions about how language speaking persuasively defines the persuasiveness of a review. User behavior simulations and controlled experiments evaluate the time-critical nature of these reviews to provide effective overviews of how consumers respond to review content and design.

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Publication Details

Journal
Journal of Informatics Education and Research
Published
2025-02-15
DOI
https://doi.org/10.52783/jier.v5i1.2179
Primary Topic
Digital Marketing and Social Media
Type
article
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article

Influence of Consumer Psychology on Mobile Reviews and Their Persuasive Impact

Dipanwita Dey
Journal of Informatics Education and Research
Digital Marketing and Social Media
article

Influence of Consumer Psychology on Mobile Reviews and Their Persuasive Impact

Dipanwita Dey
article en

Abstract

The research therefore does an empirical literature review to build the theoretical framework based on the symptoms that it seeks to investigate in mobile phone reviews. This leads to the finding that psychological biases do not only have an impact on the content creation but also on the subsequent persuasion on further consumers. In method, the content analysis is used to analyze user reviews and sentiment analysis to examine the emotional and language features. Hypothesis testing is also carried out in order to assess the impact of structural variations to the reviews on decision-making in purchase scenarios. In particular, by analyzing empirical data, the study identifies that consumer reviews are not only full of experience descriptions but also contain various biases. For example, anchoring biases can be observed when the initial reference to the price of a particular mobile phone is made when performing a review, all subsequent information will be processed with a primary emphasis on the price. In reviews consumers confirm a first impression of product being positive or negative with focus on aspects reinforcing that initial impression. Another of such important factors towards influence is Availability heuristic whereby prospective buyers would be influenced more by those reviews readily available with rather salient experiences which could be explained by the Freshness and recency effect. It also explores how other aspects of the platform that differentiate them influence consumer behaviour including basic features like social proof, time factor about the reviews or the visibility of certain reviews as recommended reviews given by buyers with high engagement or those who passed through the verification process. These problems are especially true where algorithms are used to promote specific reviews, and therefore, make them more relevant to a potential buyer. The research presented here indicates that consumers are not averse to such biases and that like when reading the reviews, these biases impinge on the writing of the reviews as well. They also pointed out that while consumers who are familiar with these biases might be better off in terms of making more rational decisions, the ones who were not exposed to such biases might be influenced to easily by the so called ‘gut feeling’ reviews which are also those, which seem to get the most attention. Altogether, this study offers fine-grained timeworn and fresh insights into the relationship between consumer psychology and online content to map out how and to what extent psychological effects influence consumer-generated content and the importance of raising awareness and implementing different mitigations to help consumers make a more rational decision. A clear focus of the study is to examine platform-mediated factors and their impact in the review ecosystem. A prominent problem is that algorithms that are designed to promote ‘useful’ or ‘more informative’ product reviews may enhance prejudiced material, especially as their calibration is guided by engagement metrics rather than the quality of information. This means that about the quality of the reviews, it will not present a balanced view in its algorithms which are likely to mislead consumers to go for the engaging but informative or biased content. The study uses quantitative analysis with natural language processing, together with qualitative analysis and behavioral mimicking. It is possible to determine emotional and cognitive bias regularities of mass mobile phone reviews by using elements of sentiment analysis. Psycholinguistic modeling extends the examination of the connection between semantic and syntactic variables to review persuasiveness and may offer perceptions about how language speaking persuasively defines the persuasiveness of a review. User behavior simulations and controlled experiments evaluate the time-critical nature of these reviews to provide effective overviews of how consumers respond to review content and design.

Journal of Informatics Education and ResearchVol. 5(1)
Ramakrishna Mission Vivekananda Educational and Research Institute (IN), Swami Vivekanand College of Pharmacy (IN)
Openalex Percentile: Top 97%
Digital Marketing and Social Media
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